Rolling grouped cumulative sum

Question

I'm looking to create a rolling grouped cumulative sum. I can get the result via iteration, but wanted to see if there was a more intelligent way.

Here's what the source data looks like:

Per C   V
1   c   3
1   a   4
1   c   1
2   a   6
2   b   5
3   j   7
4   x   6
4   x   5
4   a   9
5   a   2
6   c   3
6   k   6

Here is the desired result:

Per C   V
1   c   4
1   a   4
2   c   4
2   a   10
2   b   5
3   c   4
3   a   10
3   b   5
3   j   7
4   c   4
4   a   19
4   b   5
4   j   7
4   x   11
5   c   4
5   a   21
5   b   5
5   j   7
5   x   11
6   c   7
6   a   21
6   b   5
6   j   7
6   x   11
6   k   6

Answer 1

This is a very interesting problem. Try below to see if it works for you.

(
    pd.concat([df.loc[df.Per<=i][['C','V']].assign(Per=i) for i in df.Per.unique()])
    .groupby(by=['Per','C'])
    .sum()
    .reset_index()
)

Out[197]: 
    Per  C   V
0     1  a   4
1     1  c   4
2     2  a  10
3     2  b   5
4     2  c   4
5     3  a  10
6     3  b   5
7     3  c   4
8     3  j   7
9     4  a  19
10    4  b   5
11    4  c   4
12    4  j   7
13    4  x  11
14    5  a  21
15    5  b   5
16    5  c   4
17    5  j   7
18    5  x  11
19    6  a  21
20    6  b   5
21    6  c   7
22    6  j   7
23    6  k   6
24    6  x  11